Articles | Volume 17, issue 11
https://doi.org/10.5194/essd-17-6097-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-6097-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
13 Nov 2025
Data description article |
| 13 Nov 2025
| 13 Nov 2025
Concentration changes of atmospheric F-gases and analysis of their potential sources at Zhongshan Station, Antarctica, 2021
Ruiqi Nan
State Key Laboratory of Disaster Weather Science and Technology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
College of Geography and Environment, Shandong Normal University, Jinan, 250014, China
Biao Tian
CORRESPONDING AUTHOR
State Key Laboratory of Disaster Weather Science and Technology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
School of Earth and Space Sciences, Peking University, Beijing, 100871, China
Xinfeng Ling
Shouxian Meteorological Bureau, Huainan, 232000, China
Weijun Sun
College of Geography and Environment, Shandong Normal University, Jinan, 250014, China
Yixi Zhao
State Key Laboratory of Disaster Weather Science and Technology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Dongqi Zhang
State Key Laboratory of Disaster Weather Science and Technology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Chuanjin Li
Polar Research Institute of China, Shanghai, 200136, China
Xin Wang
State Key Laboratory of Disaster Weather Science and Technology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Jie Tang
State Key Laboratory of Disaster Weather Science and Technology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Bo Yao
CORRESPONDING AUTHOR
Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences, Fudan University, Shanghai, 200438, China
Meteorological Observation Centre of China Meteorological Administration, Beijing, 100081, China
Key Laboratory of Polar Atmosphere–ocean-ice System for Weather and Climate, Ministry of Education of the People's Republic of China, Shanghai, 200438, China
Minghu Ding
State Key Laboratory of Disaster Weather Science and Technology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Key Laboratory of Polar Atmosphere–ocean-ice System for Weather and Climate, Ministry of Education of the People's Republic of China, Shanghai, 200438, China
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-677, https://doi.org/10.5194/essd-2026-677, 2026
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Airborne particles affect air quality and climate, but their distribution with height is poorly documented over central China. We used seven years of continuous ground-based lidar observations to build a detailed record of dust and other particles profiles from 2018 to 2024. Most particles were found below about two kilometres, with dust more common in spring and other particles in winter. The dataset can help track air pollution and dust transport and improve satellite and model assessments.
Biao Tian, Minghu Ding, Kongju Zhu, Xu Yao, Yixi Zhao, Wenqian Zhang, Diyi Yang, Weijun Sun, Yining Yu, Shoudong Zhao, Yige Cui, Chuanjin Li, Jie Tang, Cunde Xiao, Tong Zhu, and Renhe Zhang
Atmos. Meas. Tech., 19, 5683–5695, https://doi.org/10.5194/amt-19-5683-2026, https://doi.org/10.5194/amt-19-5683-2026, 2026
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Jiawei Yan, Lu Zhang, Yizhou Xu, Xinfeng Ling, Weiwei Ding, Yubin Li, Yuan Wang, and Yuanjian Yang
EGUsphere, https://doi.org/10.5194/egusphere-2026-3201, https://doi.org/10.5194/egusphere-2026-3201, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Paddy fields play an important role in greenhouse gas budgets and carbon cycling. Based on in-situ observation, we found that under calm nighttime conditions, weak turbulent mixing renders carbon dioxide and methane accumulate near the surface, whereas short bursts of turbulence rapidly disperse them upward. This transport processes cannot be fully described by conventional physical framework due to the influence of submeso motions. The understanding is helpful to improve the relevant models.
Jiayi Sun, Junmei Lv, Haoran Li, Wenqian Zhang, Biao Tian, and Minghu Ding
The Cryosphere, 20, 4049–4059, https://doi.org/10.5194/tc-20-4049-2026, https://doi.org/10.5194/tc-20-4049-2026, 2026
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This study reports two years of Micro Rain Radar observations from Great Wall Station, from March 2024 to February 2026. Near-surface precipitation and snowfall occurred during 32 % and 21 % of the time. The signal changed little with height, suggesting frequent shallow snowfall. Weak winds had little effect, while stronger winds likely affected radar observations below 0.7 km. A radar-based snowfall estimate shows that the ERA5 reanalysis product underestimates cumulative snowfall.
Qiao Liu, Yongsheng Yin, Jiawei Yang, Yunyi Luo, Xueyuan Lu, Hao Wang, Yin Fu, Bo Zhang, Qianqian Zheng, Dongyu Lei, Xin Wang, Shiyin Liu, Yong Nie, and Shichang Kang
EGUsphere, https://doi.org/10.5194/egusphere-2026-2674, https://doi.org/10.5194/egusphere-2026-2674, 2026
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Xiyue Zhang, Minghu Ding, Diyi Yang, Bin Cheng, Ian Allison, Kongju Zhu, Yuande Yang, Xiangbin Cui, Petra Heil, Chuanjin Li, and Cunde Xiao
EGUsphere, https://doi.org/10.5194/egusphere-2026-2150, https://doi.org/10.5194/egusphere-2026-2150, 2026
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Stake measurements underestimate Antarctic surface mass balance (SMB) due to firn compaction. Using a firn densification model, we correct 2008-2024 stake records from Dome A. The corrected mean annual SMB is 24.14 kg m-2 yr-1, 8.8 % higher than uncorrected values, whereas RACMO2.4p1 gives 17.50 kg m-2 yr-1. The net vapor flux is equivalent to 5.7 % of the total mass input. This framework provides observational benchmarks for climate models, and supports oldest‑ice drilling at Dome A.
Jialu Liu, Pengfei Han, Huiling Ouyang, Ning Zeng, Zhenfeng Wang, Jian Wang, Weiwei Fu, Honggang Lv, Wenhao Lin, Zheng Xia, and Bo Yao
Atmos. Meas. Tech., 19, 2837–2854, https://doi.org/10.5194/amt-19-2837-2026, https://doi.org/10.5194/amt-19-2837-2026, 2026
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This study deployed a buoy equipped with three low-cost sensors in the northern South China Sea to continuously monitor atmospheric CO2 at the sea surface. After correcting for environmental factors and sensor drift, the measurement accuracy improved. CO2 levels were generally stable with small daily changes, while local fluctuations reflected air from land. This affordable approach enables reliable ocean CO2 monitoring and helps study the ocean’s role in the global carbon cycle.
Chengyan Liu, Zhaomin Wang, Dake Chen, Xianxian Han, Hengling Leng, Xi Liang, Liangjun Yan, Xiang Li, Craig Stevens, Andrew McC. Hogg, Kazuya Kusahara, Kaihe Yamazaki, Kay I. Ohshima, Meng Zhou, Xiao Cheng, Dongxiao Wang, Changming Dong, Jiping Liu, Qinghua Yang, Xichen Li, Ruibo Lei, Minghu Ding, Zhaoru Zhang, Dujuan Kang, Di Qi, Tongya Liu, Jihai Dong, Lu An, Ru Chen, Tong Zhang, Xiaoming Hu, Bo Han, Haibo Bi, Qi Shu, Longjiang Mu, Shiming Xu, Hu Yang, Hailong Liu, Tingfeng Dou, Zhixuan Feng, Lei Zheng, Xueyuan Tang, Guitao Shi, Yongqing Cai, Bingrui Li, Yang Wu, Xia Lin, Wenjin Sun, Yu Liu, Kai Yu, Yu Zhang, Weizeng Shao, Xiaoyu Wang, Shaojun Zheng, Chengyi Yuan, Chunxia Zhou, Jian Liu, Yang Liu, Yue Xia, Xiaoyu Pan, Jiabao Zeng, Kechen Liu, Jiahao Fan, Chen Cheng, and Qi Li
Geosci. Model Dev., 19, 2985–3033, https://doi.org/10.5194/gmd-19-2985-2026, https://doi.org/10.5194/gmd-19-2985-2026, 2026
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Shuyu Zhao, Tian Feng, Xuexi Tie, Biao Tian, Xiao Hu, Bo Hu, Dong Yang, Sinan Gu, and Minghu Ding
Atmos. Chem. Phys., 25, 12483–12496, https://doi.org/10.5194/acp-25-12483-2025, https://doi.org/10.5194/acp-25-12483-2025, 2025
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Atmos. Chem. Phys., 25, 4965–4988, https://doi.org/10.5194/acp-25-4965-2025, https://doi.org/10.5194/acp-25-4965-2025, 2025
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Yueli Chen, Yun Xie, Xingwu Duan, and Minghu Ding
Earth Syst. Sci. Data, 17, 1265–1274, https://doi.org/10.5194/essd-17-1265-2025, https://doi.org/10.5194/essd-17-1265-2025, 2025
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Lijing Chen, Lei Zhang, Yong She, Zhaoliang Zeng, Yu Zheng, Biao Tian, Wenqian Zhang, Zhaohui Liu, Huizheng Che, and Minghu Ding
Atmos. Chem. Phys., 25, 727–739, https://doi.org/10.5194/acp-25-727-2025, https://doi.org/10.5194/acp-25-727-2025, 2025
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Zhuang Wang, Chune Shi, Hao Zhang, Xianguang Ji, Yizhi Zhu, Congzi Xia, Xiaoyun Sun, Xinfeng Lin, Shaowei Yan, Suyao Wang, Yuan Zhou, Chengzhi Xing, Yujia Chen, and Cheng Liu
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Tianming Ma, Zhuang Jiang, Minghu Ding, Pengzhen He, Yuansheng Li, Wenqian Zhang, and Lei Geng
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Na Li, Ruibo Lei, Petra Heil, Bin Cheng, Minghu Ding, Zhongxiang Tian, and Bingrui Li
The Cryosphere, 17, 917–937, https://doi.org/10.5194/tc-17-917-2023, https://doi.org/10.5194/tc-17-917-2023, 2023
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Yetang Wang, Xueying Zhang, Wentao Ning, Matthew A. Lazzara, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Paolo Grigioni, Petra Heil, Elizabeth R. Thomas, David Mikolajczyk, Lee J. Welhouse, Linda M. Keller, Zhaosheng Zhai, Yuqi Sun, and Shugui Hou
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Minghu Ding, Xiaowei Zou, Qizhen Sun, Diyi Yang, Wenqian Zhang, Lingen Bian, Changgui Lu, Ian Allison, Petra Heil, and Cunde Xiao
Earth Syst. Sci. Data, 14, 5019–5035, https://doi.org/10.5194/essd-14-5019-2022, https://doi.org/10.5194/essd-14-5019-2022, 2022
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The PANDA automatic weather station (AWS) network consists of 11 stations deployed along a transect from the coast (Zhongshan Station) to the summit of the East Antarctic Ice Sheet (Dome A). It covers the different climatic and topographic units of East Antarctica. All stations record hourly air temperature, relative humidity, air pressure, wind speed and direction at two or three heights. The PANDA AWS dataset commences from 1989 and is planned to be publicly available into the future.
Jizu Chen, Wentao Du, Shichang Kang, Xiang Qin, Weijun Sun, Yang Li, Yushuo Liu, Lihui Luo, and Youyan Jiang
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-179, https://doi.org/10.5194/tc-2022-179, 2022
Preprint withdrawn
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This study developed a dynamic deposition model of light absorbing particles (LAPs), which coupled with a surface energy and mass balance model. Based on the coupled model, we assessed atmospheric deposited BC effect on glacier melting, and quantified global warming and increment of emitted black carbon respective contributions to current accelerated glacier melting.
Yueli Chen, Xingwu Duan, Minghu Ding, Wei Qi, Ting Wei, Jianduo Li, and Yun Xie
Earth Syst. Sci. Data, 14, 2681–2695, https://doi.org/10.5194/essd-14-2681-2022, https://doi.org/10.5194/essd-14-2681-2022, 2022
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We reconstructed the first annual rainfall erosivity dataset for the Tibetan Plateau in China. The dataset covers 71 years in a 0.25° grid. The reanalysis precipitation data are employed in combination with the densely spaced in situ precipitation observations to generate the dataset. The dataset can supply fundamental data for quantifying the water erosion, and extend our knowledge of the rainfall-related hazard prediction on the Tibetan Plateau.
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Short summary
This study presents the first dataset of 11 fluorinated greenhouse gases observed in 2021 at Zhongshan Station, Antarctica. The concentrations of most gases increased and were higher than at two other Antarctic stations. Their sources were linked to industrial activities such as refrigeration and electronics. Although limited to one year, the data provide important background information for detecting future changes in the Antarctic atmosphere.
This study presents the first dataset of 11 fluorinated greenhouse gases observed in 2021 at...
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